The invention provides a natural language emotion analysis method based on a depth network. On the basis of a memory network, semantic dependent information is introduced to guide the execution of theattention mechanism, and the context moment information including the whole emotion information of a sentence is also used to provide background information for the current analysis object word. Thewhole model includes an embedding module, a memory sequence building module, a semantic dependency mask attention module, a context moment affective learning module and an output module. In the model,the semantic dependency information of object words and context obtained from dependency syntax tree is introduced into the memory network, so that the memory sequences of each layer are generated dynamically, which leads to the execution of attention mechanism in the multi-layer module of the memory network. In addition, in order to introduce the whole affective information of a sentence, that is, the relationship information between all the object words in the same sentence, we propose a context-based learning task, which assists the affective analysis of specific object words by multitasking learning.